Key result
Information theory metrics can quantitatively assess spatially heterogeneous electrical communication and localize the drifting core of spiral reentry in cardiac arrhythmia models.
Information theory metrics can quantitatively assess electrical communication in the heart, potentially identifying optimal targets for therapeutic ablation in complex arrhythmias.
May guide ablation targeting in reentry; leaves open validation in vivo and clinical translation.
Electrical communication between cardiomyocytes can be perturbed during arrhythmia, but these perturbations are not captured by conventional electrocardiographic metrics. We developed a theoretical framework to quantify electrical communication using information theory metrics in two-dimensional cell lattice models of cardiac excitation propagation. The time series generated by each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon entropy for each cell was calculated from the time series during four clinically important heart rhythms: normal heartbeat, anatomical reentry, spiral reentry and multiple reentry. We also used mutual information to perform spatial profiling of communication during these cardiac arrhythmias. We found that information sharing between cells was spatially heterogeneous. In addition, cardiac arrhythmia significantly impacted information sharing within the heart. Entropy localized the path of the drifting core of spiral reentry, which could be an optimal target of therapeutic ablation. We conclude that information theory metrics can quantitatively assess electrical communication among cardiomyocytes. The traditional concept of the heart as a functional syncytium sharing electrical information cannot predict altered entropy and information sharing during complex arrhythmia. Information theory metrics may find clinical application in the identification of rhythm-specific treatments which are currently unmet by traditional electrocardiographic techniques.
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Ashikaga et al. (2015) studied Cardiac arrhythmia. Information theory metrics (Shannon entropy and mutual information) was evaluated on Quantification of electrical communication and spatial profiling. Information theory metrics can quantitatively assess spatially heterogeneous electrical communication and localize the drifting core of spiral reentry in cardiac arrhythmia models.
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